I am a Mechanical Engineering undergraduate at Southwest Petroleum University, focused on robotics, autonomous navigation, LiDAR-SLAM, motion planning, and control systems.
I build simulation-first robotics projects that make algorithms observable and comparable: same environment, same start and goal, measurable planner performance, reproducible outputs, and clear visual evidence. My long-term goal is a research-based MASc/MSc in autonomous mobile robots, control, navigation, or SLAM.
- Current work: multi-algorithm robot navigation using A*, Dijkstra, RRT, RRT*, PRM, DWA, LiDAR, and SLAM
- Engineering approach: model → simulate → measure → compare → improve
- Research direction: uncertainty-aware mapping, safe planning, sensor anomalies, and resilient robot decision-making
- Learning track: ROS 2, Gazebo, Nav2, SLAM Toolbox, perception, localization, and sensor fusion
| Area | What I work on |
|---|---|
| Perception & Mapping | 2D LiDAR, occupancy grids, live SLAM, camera pipelines, and environment representation |
| Planning | A*, Dijkstra, PRM, RRT, RRT*, local planning, and comparative benchmarking |
| Control | PID, LQR, fuzzy control, DWA, nonlinear control, trajectory tracking, and differential-drive motion |
| Robotics Systems | ROS 2 nodes, topics, services, actions, TF2, URDF/Xacro, ros2_control, Gazebo, RViz, and Arduino prototyping |
| Reliability | Sensor uncertainty, anomaly-aware navigation, safe behavior, reproducible evaluation, and failure analysis |
| Project | Engineering scope | Evidence produced |
|---|---|---|
| Multi-Algorithm Robot Navigation | Compares A*, Dijkstra, RRT, RRT*, and PRM in a shared MATLAB environment with a common DWA local controller, LiDAR sensing, and live SLAM. | Synchronized simulations, planner metrics, trajectories, occupancy maps, images, CSV results, and videos |
| 3D UGV Trajectory Tracking | Adaptive nonlinear control for 3D unmanned-ground-vehicle trajectory tracking in MATLAB. | Tracking response, controller behavior, and simulation plots |
| PID-Controlled Quadcopter Simulation | Cascaded PID control for nonlinear quadcopter trajectory tracking using MATLAB/Simulink. | Closed-loop simulation and trajectory tracking results |
| PID–LQR–Fuzzy Mobile Robot Tracking | Comparative study of PID, LQR, and fuzzy-logic controllers for mobile-robot trajectory tracking. | Controller comparison, error behavior, and MATLAB visualizations |
| Advanced Mobile Robot Navigation | Autonomous mobile-robot navigation with path planning, DWA, LiDAR, SLAM, and route tracking. | Navigation trajectories, mapping results, and simulation outputs |
| SLAM Live Occupancy Map | Differential-drive robot simulation using A*, DWA, 360° LiDAR, route locking, and live occupancy mapping. | Live SLAM map, explored-space metrics, and recorded navigation |
New repositories automatically appear on the complete projects page. Featured projects above are selected manually.
flowchart LR
A["Global planner<br/>A* · Dijkstra · PRM · RRT · RRT*"]
B["Reference path<br/>waypoints + route"]
C["Local control<br/>DWA / tracking controller"]
D["Robot simulation<br/>differential drive"]
E["Sensors & state<br/>LiDAR · odometry · pose"]
F["Mapping & evaluation<br/>SLAM · metrics · plots"]
A --> B --> C --> D --> E --> F
E --> C
F --> A
- Build a complete ROS 2 mobile-robot stack with URDF/Xacro, TF2, Gazebo, RViz, ros2_control, LiDAR, camera, and IMU
- Integrate SLAM Toolbox, Nav2, AMCL, and robot_localization for mapping, planning, localization, and sensor fusion
- Reimplement selected planning and control components in Python and C++ for ROS 2
- Extend navigation experiments toward uncertainty-aware mapping, sensor-anomaly handling, and safe decision-making
- Publish reproducible experiments with configuration files, metrics, videos, limitations, and failure cases
ROS 2 Jazzy · Gazebo Harmonic · Nav2 · SLAM Toolbox · TF2 · URDF/Xacro · ros2_control · OpenCV · Arduino Integration · EKF/UKF Sensor Fusion · Safe Motion Planning · Robot Learning
“Build robots that can sense uncertainty, plan safely, and explain why they move.”
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